AIMC Topic: Algorithms

Clear Filters Showing 6261 to 6270 of 28713 articles

LightNet: A Novel Lightweight Convolutional Network for Brain Tumor Segmentation in Healthcare.

IEEE journal of biomedical and health informatics
Diagnosis, treatment planning, surveillance, and the monitoring of clinical trials for brain diseases all benefit greatly from neuroimaging-based tumor segmentation. Recently, Convolutional Neural Networks (CNNs) have demonstrated promising results i...

Prediction of PM concentration based on a CNN-LSTM neural network algorithm.

PeerJ
Fine particulate matter (PM) is a major air pollutant affecting human survival, development and health. By predicting the spatial distribution concentration of PM, pollutant sources can be better traced, allowing measures to protect human health to b...

Protein ligand binding site prediction using graph transformer neural network.

PloS one
Ligand binding site prediction is a crucial initial step in structure-based drug discovery. Although several methods have been proposed previously, including those using geometry based and machine learning techniques, their accuracy is considered to ...

Iteratively Calibratable Network for Reliable EEG-Based Robotic Arm Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Robotic arms are increasingly being utilized in shared workspaces, which necessitates the accurate interpretation of human intentions for both efficiency and safety. Electroencephalogram (EEG) signals, commonly employed to measure brain activity, off...

Predicting telomerase reverse transcriptase promoter mutation in glioma: A systematic review and diagnostic meta-analysis on machine learning algorithms.

The neuroradiology journal
BackgroundGlioma is one of the most common primary brain tumors. The presence of the telomerase reverse transcriptase promoter (pTERT) mutation is associated with a better prognosis. This study aims to investigate the TERT mutation in patients with g...

DEAF-Net: Detail-Enhanced Attention Feature Fusion Network for Retinal Vessel Segmentation.

Journal of imaging informatics in medicine
Retinal vessel segmentation is crucial for the diagnosis of ophthalmic and cardiovascular diseases. However, retinal vessels are densely and irregularly distributed, with many capillaries blending into the background, and exhibit low contrast. Moreov...

The heart sound classification of congenital heart disease by using median EEMD-Hurst and threshold denoising method.

Medical & biological engineering & computing
Heart sound signals are vital for the machine-assisted detection of congenital heart disease. However, the performance of diagnostic results is limited by noise during heart sound acquisition. A limitation of existing noise reduction schemes is that ...

Multi-step framework for glaucoma diagnosis in retinal fundus images using deep learning.

Medical & biological engineering & computing
Glaucoma is one of the most common causes of blindness in the world. Screening glaucoma from retinal fundus images based on deep learning is a common method at present. In the diagnosis of glaucoma based on deep learning, the blood vessels within the...

Few-shot learning with representative global prototype.

Neural networks : the official journal of the International Neural Network Society
Few-shot learning is often challenged by low generalization performance due to the model is mostly learned with the base classes only. To mitigate the above issues, a few-shot learning method with representative global prototype is proposed in this p...

Artificial Intelligence and Ophthalmic Clinical Registries.

American journal of ophthalmology
PURPOSE: The recent advances in artificial intelligence (AI) represent a promising solution to increasing clinical demand and ever limited health resources. Whilst powerful, AI models require vast amounts of representative training data to output mea...